RealTest Mean Reversion Trading Strategy
A RealTest mean-reversion strategy for S&P 500 stocks that waits for a candlestick reversal before buying an oversold name, so entries come only after sellers start to step back. Tested on survivorship-bias-free Norgate data, with Interactive Brokers commissions and limit fills modeled, and trading live since May 2024.
Live traded since May 2024Trading costs included
Survivorship-bias-free data
Strategy
SPY buy & hold
Sharpe ratio?
1.4
+192%vs SPY 0.48
Best year?
+86.0%
3.2×SPY best: 27.0% in 2003
Max drawdown?
-15.5%
69% smallervs SPY -49.9%
Validated four ways
Live market performance
Performs in real market conditions since 2024-05-01
VerifiedStatistical validation
Validated across in-sample & out-of-sample data
Walk forward analysis
Tests robustness across unseen data
Monte Carlo stress test
Resilient against 1,000+ sequence risk simulations
What happened in every crash
| Crisis | Dates | Strategy | SPY | Same $100k in |
|---|---|---|---|---|
| Dotcom crash | Mar 2000 – Oct 2002 | 169.8% | -41.8% | |
| 2008 financial crisis | Oct 2007 – Mar 2009 | 12.5% | -49.9% | |
| COVID-19 crash | Feb 2020 – Mar 2020 | -5.1% | -28.7% | |
| 2022 bear market | Jan 2022 – Oct 2022 | 4.1% | -21.3% |
Strategy monthly returns
| Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | Year | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2000 | -2.3 | 7.9 | 4.3 | 5.4 | 9.6 | 1.8 | 3.0 | 8.5 | 1.9 | 14.7 | 6.0 | 3.9 | 86.0% |
| 2001 | 5.8 | 7.5 | 1.4 | 1.6 | 0.0 | 2.1 | 2.5 | 2.3 | -2.0 | 6.5 | -0.4 | 5.5 | 37.7% |
| 2002 | 3.0 | -2.2 | 3.3 | 3.2 | 2.6 | -0.5 | -1.4 | 0.3 | 3.8 | 0.7 | 2.4 | 3.1 | 19.7% |
| 2003 | 2.8 | 0.6 | 1.4 | 0.8 | 6.8 | 9.1 | 4.3 | 3.6 | -0.8 | 7.7 | 5.4 | 1.3 | 51.8% |
| 2004 | 1.0 | 4.1 | 2.3 | -1.2 | 1.1 | 0.2 | -2.1 | 0.6 | 0.9 | 1.7 | -1.0 | 3.4 | 11.2% |
| 2005 | -6.3 | 2.1 | 2.9 | 1.0 | 1.9 | 1.8 | 3.4 | 0.0 | 1.5 | -1.2 | 1.4 | 1.6 | 9.9% |
| 2006 | 4.2 | 2.6 | 3.9 | 3.1 | -5.0 | 1.2 | 1.4 | 0.4 | -0.5 | 3.2 | 0.6 | -0.2 | 15.7% |
| 2007 | -0.2 | -1.9 | 1.8 | 3.0 | 1.6 | 4.0 | 1.2 | 3.3 | -0.1 | 4.0 | 0.5 | 3.2 | 22.2% |
| 2008 | -7.7 | 0.9 | 3.7 | 2.2 | 5.7 | 2.9 | -2.6 | 0.5 | 8.2 | -1.0 | 0.0 | 0.0 | 12.5% |
| 2009 | -0.1 | -5.4 | -0.3 | 6.6 | 3.5 | 4.0 | -1.8 | 3.1 | 9.1 | -4.7 | 5.1 | 1.6 | 21.4% |
| 2010 | -4.2 | 5.4 | 2.1 | 1.4 | 0.8 | -2.0 | 1.0 | 2.1 | 0.0 | 2.5 | 0.9 | 2.0 | 12.4% |
| 2011 | -0.0 | 2.8 | 5.2 | 1.3 | 2.7 | -0.9 | 1.2 | -3.5 | 1.4 | 2.6 | -1.1 | 0.7 | 12.7% |
| 2012 | 0.8 | 1.5 | 3.9 | 1.9 | -1.2 | 1.8 | 1.5 | 0.8 | 0.9 | 3.9 | 1.3 | 1.0 | 19.6% |
| 2013 | 0.3 | 3.6 | -0.0 | 1.5 | 0.8 | 3.3 | 0.2 | 0.6 | 1.4 | 4.1 | 0.9 | 0.3 | 18.2% |
| 2014 | -2.1 | 1.0 | 0.8 | 4.9 | 0.6 | 0.3 | -2.3 | 0.5 | 0.8 | -1.6 | 0.2 | 2.3 | 5.4% |
| 2015 | 3.9 | 1.0 | 0.6 | -1.4 | 3.4 | 3.2 | 0.9 | 0.6 | 0.4 | 0.3 | 1.8 | 0.3 | 15.9% |
| 2016 | -1.1 | 0.9 | 2.2 | 0.8 | 0.3 | 3.7 | 0.9 | -3.1 | 1.7 | 0.9 | 2.5 | -0.2 | 9.7% |
| 2017 | 0.9 | -0.7 | -0.0 | 0.7 | -0.3 | 1.5 | 0.2 | -0.2 | 1.1 | 2.4 | 0.9 | 1.2 | 8.1% |
| 2018 | 0.7 | -0.9 | 3.8 | 0.6 | 4.5 | 1.7 | -0.8 | 1.5 | -1.1 | -0.9 | 2.5 | -1.5 | 10.3% |
| 2019 | -0.2 | 0.2 | 1.3 | 1.4 | -5.6 | 2.4 | -0.5 | 0.0 | 1.3 | 4.4 | 0.1 | 2.1 | 6.6% |
| 2020 | -1.7 | -4.9 | 4.1 | -0.0 | 3.7 | 7.2 | 8.3 | 2.1 | 1.6 | -1.1 | 4.1 | 2.8 | 28.6% |
| 2021 | -4.6 | 5.8 | 0.5 | 0.9 | 3.7 | -0.2 | -1.7 | 3.3 | -0.5 | -0.4 | 1.7 | 9.9 | 19.1% |
| 2022 | -4.9 | 2.4 | 8.5 | -0.2 | 5.4 | -8.9 | -0.9 | 1.0 | 1.7 | 1.0 | 7.9 | -1.0 | 11.3% |
| 2023 | 1.4 | -0.4 | -2.3 | 0.2 | -0.9 | 2.1 | 4.9 | 0.7 | -1.9 | 0.5 | 0.9 | 1.8 | 7.2% |
| 2024 | 2.4 | 7.2 | 4.0 | 1.5 | 3.0 | 1.5 | -2.2 | 1.1 | 0.6 | 1.4 | 6.8 | 2.6 | 34.0% |
| 2025 | 1.8 | -2.7 | -2.5 | -3.5 | 0.2 | 3.0 | 3.6 | 4.3 | 3.8 | 2.8 | -1.0 | 3.8 | 14.1% |
| 2026 | 2.5 | 4.9 | -1.3 | -0.0 | 7.3 | 1.6 | 5.8 | 2.2 | 0.5 | 25.7% |
Strategy overview
Specification
StyleMean reversionUniverseS&P 500 current & past stocksTimeframeDailySideLongAverage hold6 trading daysTrade frequency10.8 per monthEntry executionLimit orderExit executionLimit & marketDataNorgate Data (US Stocks Platinum)
SoftwareRealTestCommission$0.005 / shareLimit price buffer0.05% past limitSPY benchmarkNo fees applied (favors SPY)
What you get
RealTest strategy code (.rts)
Complete RealTest (.rts) strategy code. Import, backtest, and modify.
Plain text rules
Trade it on any platform without reading the code.
Quick start & live trading
Quick start guide
From download to first backtest in 1 minute
1
You download the .rts file
Click download
2
You open it in RealTest
File → Open → Select file
3
You import symbols
Click import
4
You run the backtest
Click test
Daily live trading
For RealTest automated execution
1
Open OrderClerk
Click 'Connect to IB'
2
Import signals
Click 'Import' in RealTest
3
Generate orders
Click 'Orders' in RealTest
4
Execute trades
Click 'Place Orders'
What traders say
❝
Buying a SetupAlpha strategy didn't save me money, it saved me research time. I estimate it replaced 70–90 hours of development, debugging, and validation. Even if I never trade the strategy exactly as delivered, the research process was worth the investment.
Roman Blackwood
Founder of AI in Trading (+13K subscribers)
❝
I've been using a strategy from SetupAlpha and I'm really impressed with its elegance and stability. The unique approach gives me a fresh perspective and ideas I can apply to other strategies I'm developing. I'm currently working on integrating it into my suite of trading strategies.
TradeQuantiX
Multi-country systematic trader (+4.7K subscribers)
❝
I traded discretionary for over a decade and kept putting off going systematic because I did not know where to start. Having a finished, tested system to take apart was what finally got me moving.
Daniel
Crypto trader
❝
I have run it live since 2024 and it is still in my portfolio. It also changed how I test the systems I build myself.
Systematic Traders
Algo trader & Substack writer (+6.4K subscribers)
FAQ
What is RealTest Mean Reversion Trading Strategy?
A RealTest mean-reversion strategy for S&P 500 stocks that waits for a candlestick reversal before buying an oversold name, so entries come only after sellers start to step back. Tested on survivorship-bias-free Norgate data, with Interactive Brokers commissions and limit fills modeled, and trading live since May 2024.
Why should this edge keep working?
Buying a stock only because it is oversold can mean buying one that keeps falling. This strategy waits for a candlestick reversal, a price-action sign that sellers are losing control, before it enters. The entry comes after the first evidence of stabilization rather than in the middle of the decline. Waiting for buyers to show up is a standard way to raise entry quality in mean reversion, not a one-time trick.
What is RealTest and what software do I need?
RealTest is a backtesting and trade automation platform for systematic traders, built by Martin Parker at MHP Trading. Each strategy comes as an .rts file you import directly. To trade it live you add OrderClerk and an Interactive Brokers account.
How was this backtested?
Survivorship-free Norgate data from January 2000 to the present, with out-of-sample walk-forward analysis and over 1000 Monte Carlo simulations to test stability.
Are transaction costs included?
Yes. The results include Interactive Brokers commissions, and a limit-order buffer of 0.05% past limit, so the equity curve is after costs.
When did live trading start?
Live trading started in May 2024. The equity curve shows the backtest from 2000 and real performance from that point on.
What's included in the download?
RealTest .rts file (complete source). Plain-text trading rules. Full documentation with parameter explanations.
How does it compare to SPY?
The chart at the top plots this strategy against SPY, the S&P 500 ETF, from 2000 with both starting at $100,000. A metrics table lists the exact numbers side by side: Sharpe, Sortino, net profit and worst year, for the strategy and for SPY over the same period.
Can I modify the code?
Yes. You get the complete source code with a perpetual license, so you can adjust parameters, change position sizing, combine it with other systems, or use it as a starting point for your own research.
What market data do I need?
Norgate Data (recommended) for survivorship-free US equities. Yahoo Finance works for basic testing but lacks delisted stocks. The backtest results shown here use Norgate Platinum.
Can I automate execution?
RealTest to OrderClerk to Interactive Brokers. Generate signals daily in RealTest, execute automatically via OrderClerk to IBKR. Setup course available.
Can I ask questions about the code or the strategy?
Yes. Email setupalpha.capital@gmail.com and you will get an answer, before or after you buy.
Changelog
2024-05-01Rules finalised. Live tracking starts.
No rule changes since.
Portfolio growth since 2000
11,673.1%
SPY same period: 492.5%
$999one-time
Instant download
| Metric | Strategy | SPY |
| Sharpe | 1.4 | 0.48 |
| ROR | 19.56% | – |
| Sortino | 1.35 | 0.46 |
| MAR | 1.26 | – |
| Net profit | $11.7M | $492k |
| Expectancy | 1.42% | – |
| Max exposure | 99.9% | 100% |
| Worst year | 5.4% | -33.2% |
Download the complete strategy now
Active Script - C:\REALTEST\Strategies\mean_reversion_2025.rts
Plain text rules
Trade it on any platform without reading the code.
RealTest Mean Reversion Trading Strategy
$999one-time
Instant download